Detection of bad detectors at idle state

ABSTRACT

A fault checker system for an X-ray detector, comprising an input interface (IN) for receiving readings acquired by a target detector pixel not exposed to X-radiation. A converter (CV) is configured to convert the readings into a metric. A thresholder (CP) is configured to compare the metric against at least one threshold and, based on the comparing, provide an indication on whether the detector pixel is faulty.

FIELD OF THE INVENTION

The invention relates to a fault checker system for an X-ray detector,to a method of fault-checking an X-ray detector, to an imagingarrangement, to a computer program element, and to a computer readablemedium.

BACKGROUND OF THE INVENTION

In some X-ray imaging systems (“imager”), such as computed tomographyscanners (“CT”), the X-ray detection system comprises typically tens ofthousands of detector channels, also known as pixels. It may happen thatchannels fail over the lifetime of the CT scanner. Failing channels aresometimes called Bad Detector (“BD”) (channels or pixels).

If data acquired at BDs is used in image reconstruction, artifacts mayoccur.

SUMMARY OF THE INVENTION

There may therefore be a need for improving X-ray imaging.

The object of the present invention is solved by the subject matter ofthe independent claims where further embodiments are incorporated in thedependent claims. It should be noted that the following described aspectof the invention equally applies to the method of fault-checking anX-ray detector, to the imaging arrangement, to the computer programelement and to the computer readable medium.

According to a first aspect of the invention there is provided a faultchecker system for an X-ray detector, comprising:

an input interface for receiving readings acquired by a target detectorpixel not exposed to X-radiation;

a converter configured to perform a conversion operation to convert thereadings into a metric; and

a thresholder configured to compare the metric against at least onethreshold and, based on the comparing, providing an indication onwhether the detector, in particular the target detector pixel, isfaulty.

The readings collected from the target pixel during an idle state of thedetector represent measurements of noise. Properties of noise, such asits fluctuation, or other noise patterns may be used herein to identifya faulty pixel. The fault may be in the circuitry of the detector, inparticular in a channel of the said target detector.

In embodiments, the conversion operation by the convertor includes anormalization operation applied to the readings. This allows making thethresholding, and hence the fault finding, more robust.

In embodiments, the normalization operation relates readings from agroup of one or more other pixels, to the readings acquired by thetarget pixel. This furthers robustness and allows in particularcompensating for drift effects.

In embodiments, the group of pixels neighbor the target pixel. However,readings from pixels elsewhere on the detector array may be used. Inparticular, all remaining pixels may be used or only a part thereof,etc. In embodiments, the target pixel is included in a detector tile,and wherein the neighboring pixels are restricted to the detector tile.This allows for yet better robustness of the fault finding.

In embodiments, the metric is configured to quantify a fluctuation inthe acquired readings.

In embodiments, the metric includes any one or more of: i) an estimateof an over-time standard deviation, ii) a sum of absolute differencesover time.

In embodiments, the normalization operation includes forming spatialmedians for readings in the said group of one or more pixels.

The fault checker may run once or more than once, at times betweenscans, while the scanner XI is at idle state. The fault checker may runrepeatedly (at a relatively high repetition frequencies)quasi-continuously when the imager is in idle state. The fault checkeris capable of detecting bad detector pixel.

The “idle state” as used herein is one where there is no X-ray sourceexposure of the detector. In particular, this can be achieved byswitching off the X-ray source from power supply or otherwise disablethe X-ray source to not expose the detector to X-radiation. Although oflesser preference herein, the detector may be moved out of the X-raybeam. However, switching off the X-ray source is preferred herein, andin particular keeping it switched off for a preset time between imagingduties. Whilst the X-ray source remains switched off in idle state, thedetector itself remains “on”, that is, the detector remains powered onwhilst the fault checker performs the fault check. The detector remainspowered on in the proposed idle state for fault checks so that readingscan be generated and provided at the detector's output interface.

If the fault checker identifies a new BD pixel, this BD pixel may behandled before a next clinical scan. The fault checker does not requireapplying an external signal, such as X-ray.

In embodiments, the fault checker enables detecting faults (failuremodes) such as discontinuities situated between the transducer stage(eg, photodiodes) and the digitizing circuit in the detector. Somedetector circuity includes an operation amplifier for a given channel.In embodiments, an effect of an impedance of the transducer stage (eg,photo detector array) on the standard deviation of a bias of anassociated operation amplifier is used to detect conductor linediscontinuities. The effect may include a measurable noise decrease.However, compromised conductor lines are not the only failure mode thatcan be found with the proposed fault checker. Other detectable failuremodes include shorts which manifest themselves in noise increase.

In embodiments, the fault checker may use available data paths in theimager, in particular in the detector, to collect the readings. Noadditional circuity may be required in some embodiments.

With the proposed fault checker operating in idle states, the imager maybe kept operational, despite a bad pixel being found. It may not benecessary to trigger a service call out. A fault found may be recordedfor each pixel. A service call can still be scheduled in the futurewhilst the imager remains operational until then. Downtime can bereduced or avoided altogether.

In embodiments, the system may comprise a compensator to compensate forfaulty channels during imaging, based on the output by the fault checkerthat flags up bad pixels. The output of the fault checker may include adata structure such as a table that associates a pixel address with aflag to indicate whether the pixel is bad or not.

The fault checker system may operate fully automatically “in thebackground” without user intervention and without affecting clinicworkflow.

The one or more threshold for a given (target) pixel may be dynamicallyadapted, that is updated, based on readings from other pixels. Inembodiments, the readings used for the normalization may also be usedfor the threshold adaptation. The threshold updating may be done onceup-front, or repeatedly in measurement cycles when new readings arecollected. The threshold adaptation may be conditional on certain one ormore conditions. For example, if the current metric remains under (or,in embodiments, over) the current threshold, no adaptation is performedin this cycle.

In another aspect, there is provided a method of fault-checking an X-raydetector, comprising the steps of:

receiving readings acquired by a target detector pixel not exposed toX-radiation;

converting the readings into a metric; and

comparing the metric against at least one threshold and, based on thecomparing, providing an indication on whether the detector is faulty, inparticular that the target pixel is faulty.

In another aspect, there is provided an arrangement, comprising:

an X-ray imaging apparatus; and

the system of any one of the above mentioned embodiments.

In embodiments, at least a part of the system is integrated into adetector module of the X-ray imaging apparatus.

In embodiments, the imaging apparatus is a medical X-ray imagingapparatus, in particular a computed tomography, CT, scanner.

In another aspect, there is provided a computer program element, which,when being executed by at least one processing unit, is adapted to causethe processing unit to perform the method.

In another aspect, there is provided a computer readable medium havingstored thereon the program element.

“Fault” or “faulty” as used herein refers in particular to anyunintended configuration in the circuitry of the detector that may leadto incorrect readings when the detector would be used during imaging (onX-ray exposure). The detector circuity may include in particularcircuitry that forms part, or affects, the detector channels (alsoreferred to herein as pixels). The said unintended configuration mayinclude any one or more of: corrupted conductor line(s), shorts, loosecontact(s), and other. The corrupted conductor line may include totalinterruption or intermittent interruption. The unintended configurationmay also include malfunctioning electronic components in the circuitry,such as capacitators, photodiode, resistors, or others.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the invention will now be described withreference to the following drawings, which are not to scale, wherein:

FIG. 1 shows a perspective view of an X-ray imaging apparatus;

FIG. 2A shows a schematic block diagram an X-ray detector module;

FIG. 2B shows an enlarged plan view of a two dimensional X-ray detectormodule;

FIG. 3 shows a simplified circuitry diagram of pixel circuitry in anX-ray detector module;

FIG. 4 shows a schematic block diagram of a fault checking system for anX-ray detector module;

FIG. 5 shows a flow chart for a method of fault checking an X-raydetector; and

FIG. 6 shows a plot to illustrate exemplary measurement data collectedby an X-ray detector and processed according to the method in FIG. 5 .

DETAILED DESCRIPTION OF EMBODIMENTS

With reference to FIG. 1 , there is shown a schematic perspective frontview of a medical image system XI. The medical image system ispreferably an X-ray imaging system of the rotatory type such as a CTscanner. Other rotational imaging modalities, such as C- or U- arm X-rayimaging apparatuses, or a mammography apparatus are also envisagedherein. Non-rotational imagers such as a radiography apparatus is alsoenvisaged. In short, any type of X-ray imager is envisaged herein, andthe continued reference to a CT scanner type imager XI is an exemplaryembodiment and in no way limiting the present disclosure.

In particular, but not only, CT type imagers XI may comprise astationary gantry NG set-up in an examination room. The stationarygantry NG carries a rotational gantry RG rotatable around an examinationregion A with rotation axis Z passing therethrough. The rotationalgantry is donut-shaped and the examination region A is formed as anopening therein. An examination table TB can be made to at last partlyextend into the examination region along the rotation axis Z which mayalso be referred to herein as the imaging axis Z. A patient PAT, or anobject to be imaged, resides on the examination table. The table TB withthe patient PAT thereon may be advanced along imaging axis Z so that aregion of interest comes to lie in the examination region A. Theexamination table TB is optional.

The rotational gantry includes a detector module D that is capable ofdetecting x-radiation. The rotational gantry RG may further include anX-ray source XS. The source XS may be arranged on the rotational gantryRG in opposed spatial relationship to the detector D and across theexamination region A.

During imaging, X-radiation emanates from the X-ray source XS andinteracts with patient tissue, then emerges from the patient's far end,to then impinge on the detector D. The impinged radiation is convertedby the detector D into (projection) measurement data (sometimes referredto as detector raw data). The measurement data collected at the detectorD may represent intensity values. As envisaged herein, the imager XIincludes a fault checker FS that is configured to detect a fault in thedetector module D. The fault checker is configured to operate whilst theimager XI is in an idle state outside imaging, that, whilst there is noX-radiation received that the detector. In particular, the X-ray sourceXS may be off whilst the fault checker FS operates. Operation of thefaulty checker FS will be explained more fully below at FIGS. 2-6 .

With continued reference to FIG. 1 , during imaging, the rotationalgantry rotates and with it the detector and in embodiments also theX-ray source. Due to the rotation, the measurement data can be acquiredfrom preferably a multitude of different spatial directions p relativeto the patient. In some imaging protocols, the table TB advances alongthe imaging axis Z to collect measurement data at different locations.An image plane (or “image domain”) in which image data isre-constructible from the measurement data is schematically indicated bydirections X,Y, each image plane being perpendicular to the imaging axisZ. There are different such parallel image planes, one for each locationon the Z axis. An external or on-board power supply (not shown) suppliespower to rotational gantry RG (and/or components thereon) via aslip-ring arrangement. An operator console (not shown) may allow a user(such a medical personnel) to control the imaging operation. The usermay use the operator console to issue imaging control signals such asX-ray source settings, detector settings, or signals that control speedof the rotation, movement of the table TB, etc.

The measurement data may be forwarded through a wireless or wiredcommunication arrangement to an image processing system IPS. The imageprocessing system IPS may be arranged as computer system that runsimaging software such as an image reconstruction algorithm that allowsconverting the (projection) measurement data from the projection domaininto cross sectional imagery in the image domain X,Y. A preferablymultitude of cross sectional imagery may be obtained along the imagingaxis Z which can be assembled into a 3D image volume. Other tasks may beperformed by the image processing system IPS. The image processingsystem IPS may reside on a single or a plurality of computers such as ina “Cloud” setting or other distributed architectures. Instead of, or inaddition of providing the measurement data to the image processingsystem IPS, the measurement data may be forwarded for storage to adatabase DB (such as a PACS of a HIS) or other memory. The reconstructedimagery or the measurement data may be visualized on a display device MTor may be otherwise processed.

Before turning to the proposed fault tracker system FC in more detail,reference is first made to FIG. 2 to explain operation of the X-raydetector module D. FIG. 2A is a schematic block diagram of the detectormodule D whilst

FIG. 2B furnishes a plan view (enlarged for illustration purposes) onthe detector module D when viewed from the source XS along a projectiondirection p.

Referring first FIG. 2A, the detector module includes a data acquisitionunit DAQ. The basic function of the data acquisition unit DAQ is toconvert the incoming x-radiation into electrical signals that representX-ray photon energy. The electrical signals can be converted byanalogue-to-digital (A/D)-circuitry into numbers which can then beprocessed by the image processing system IPS into imagery in imagedomain for visualization for example.

The data acquisition unit DAQ of the detector D includes a transducersection XC where X-ray photons are converted into electrical signals.The transducer section XC may be structured into a number of spatiallyarranged pixel elements PX1, PX2. An example of a 2D pixel matrix layoutwith i columns and j rows is shown in plan view in FIG. 2B. The view isalong the projection direction p which extends into the drawing plane ofFIG. 2B. 1D layouts are also envisaged in some imaging modalities suchas in mammography imagers of the slot scan type for example.

Each of the pixels PX1,PX2 is associated and coupled to respective pixelelectronics PE1, PR2. Only two pixels PX1,PX2 are shown forillustration. For example, in some CT scanner detectors, the number ofsuch pixels runs into the order of about 10⁵. The pixel electronics PE1,PE2 form read-out circuitry that provide the electrical signals in theanalogue domain through read-out lines to a shared electronic circuitrySE. Each pixel has its own read-out line. The electrical signals, avoltage or a current, is provided through the read-out lines asindividual detector pixel readings, multiple times per unit time. Theshared circuitry SE, or other, downstream circuitry, may implementconditioning tasks such as filtering, amplification etc, and includes inparticular the A/D circuitry where the analogue signals, usually involtages, are converted into numbers that can then be processed by theimage processor IPS into imagery in the image domain. The output at theshared electronic stage SE forms the above mentioned measurement rawdetector data 7E in the projection domain.

The proposed fault checker system FC is envisaged to tap into thecircuitry of the data acquisition unit DAQ, in embodiments in theanalogue domain as shown by tap points in FIG. 2A. In particular,analogue signals provided by the respective pixel electronics PE1 andPE2 are processed by the fault checker FC to establish whether there isa fault or not. Alternatively or in addition, the fault checker FC maytap into connective circuitry that couples the pixel elements PX1,PX2 inthe transducer stage to the respective pixel electronics PE1, PE2. Ingeneral, a “pixel” as used herein may refer to each individualassemblage that comprises a certain part of the transducer stage, thatis the pixel element, and its associated pixel electronics PE1,PE2 towhich the pixel element is coupled. A connection from a given pixel toits read-out line is also referred to herein as a “channel”. There areas many channels as there are pixels in a detector D.

In a preferred embodiment, and in addition or in the alternative to theabove, the readings are collected by the fault checker not (only) in theanalogue domain, but in the digital domain, that is, downstream (after)the A/D circuitry.

With these definitions, it can be said that the fault checker asenvisaged herein is configured to find a faulty pixel, and the fault mayoccur anywhere in the given assemblage or channel. A faulty pixel may bereferred to herein as a “bad detector pixel” or “bad pixel BD” orsimpler still, as “pixel is BD”.

In a preferred embodiment the detector D is of the indirect conversiontype where the converter stage XC includes a scintillator layer, usuallymade from a crystal, or any other suitable material, such as ceramics orgarnets. One side of the layer is arranged to face the incoming X-rayphotons. Underneath, that is, the other side of the scintillator layeris coupled to an array of photo-diodes PHD, each photodiode preferablyassociated with the respective pixel positions/elements PX1, PX2 in thescintillator layer. In this embodiment, the scintillator is structuredinto pixel scintillator elements. The conversion is “indirect” becauseincoming X-ray photons are first converted into visible light byoperation of the scintillator layers and it is photons in the visiblespectrum that are then converted into analogue electrical signals by thephotodiodes. Unstructured scintillators, such as mono crystals, are alsoenvisaged where there is no such one-on-one correspondence betweenscintillator elements and pixel electronics PE1, PE2. In thisembodiments, the pixel P1,P2 is defined by each of the individual pixelelectronics PE1, PE2.

The fault-checking system and associated principles disclosed herein arenot confined to indirect conversion type detectors. In particular,direct conversion type detectors are also envisaged herein. In directconversion detectors, the conversion stage XC is formed from asemi-conducting material crystal such as silicone layer, across whichpixel electrodes are mounted as part of the pixel electronics. In otherwords, electrodes for each pixel comprises an anode and a cathode. Avoltage is applied by a power source (not shown) across thesemi-conductor crystal. Incoming X-ray photons cause cloud charges to beformed. The cloud charge comprises holes and electrons. The electronsdiffuse to the anode whereas the holes diffuse to the cathode thusclosing a circuit and an electric signal issues, which then travelsalong a respective read-out line to the shared electronics SE.

In embodiments, the detector module is compiled from Individualsub-modules, or pixel tiles, rather than, as is shown in FIG. 2B,forming one monolithic structure, which however is also envisaged inother embodiments. Each tile, forms a group of pixels, and each of thepixels in a given tile are generally served by a respective sharedelectronic circuitry SE.

In general, the shared electronic circuitry SE may be implemented by anASIC or other circuitry. Read-out lines that run from pixel electroniccircuitry PE1,PE2 on a given tile are preferably coupled to the sameshared electronic circuitry and the readouts are processed by thisshared electronic circuitry.

One failure mode causing channels failures are disconnections betweenthe transducer stage XC that converts the X-ray energy to electricalsignals, and the electronic circuit input ports into the pixelelectronics PE1,PE2. One effect that is proposed herein to be harnessedin identifying such bad channels is that capacitance at the input of acharge integrating amplifier increases the noise measured by anamplifier output. The transducer stage XC, or an element thereof, addssome capacitance at the input of the amplifier that receives theelectrical signals. Discontinuities reduce the capacitance at theamplifier input, and hence such discontinuities may be identified fromthe reduction of the noise. Alternatively, another failure mode isshorts that may reduce the resistance at the input of the amplifier.Shorts may be identified from increase of noise that they cause.

In more detail, and with reference to FIG. 3 , this shows a simplifiedwiring diagram of a part of indirect conversion detection circuitry ofthe integrating type as envisaged herein in embodiments. The diagramshows an individual pixel circuitry PE1, and also including a part ofits associated pixel element PX1. In more detail, the circuity includes,in embodiments, an integrating operational amplifier OA (“OpAmp”) and aphotodiode PHD as part of pixel element PX1, the other part being aportion of the scintillator layer. The measured value is passed onwardsby the OpAmp to a read out line. In embodiments, each pixel j, and henceeach pixel electronic circuitry PE_(j), has its own read out line.

An operation mode of this circuit is as follows. After a reset operationthrough switch SW, the switch SW is opened to disconnect a resetcapacitor RC from the operational amplifier OA to start an integrationoperation to produce measurement readings. Current from either thephotodiode PHD or bias BS flows to the operational amplifier's OA inputport. The current discharges an integrating capacitor C_(int) (which wasnegatively charged). Once integrating capacitor C_(int) is discharged,the operation amplifier OA triggers a new re-charge cycle. Therefore,the number of re-charge cycles per unit time measures the current at OAinput, thus producing a (noise) measurement. Specifically, at idle state(no X-ray exposure), the photodiode PHD may be described as a capacitorat the input of the operational amplifier OA. The operational amplifierOA measures the bias current BS by integrating on C_(int). An idealoperational amplifier has infinite input impedance. The photodiode PHDcapacity at the input reduces the input impedance and increases thenoise of the bias measurement. If the photodiode PHD is disconnected insome channel, the noise of the bias measurement will be lower for thischannel. In particular, the scheme implemented by the fault checker FCallows detecting discontinuities at idle state. The location of adiscontinuity, such as an interrupted or otherwise compromisedconnecting line, is shown as a cross “x” in FIG. 3 , with arrows to theleft and right indicating other possible locations for the failurediscontinuity situated between the output of the photo detector PHD andthe input of the operation amplifier OA.

Other failure modes include shorts. Shorts, may occur when there is anunintended, abnormal, current path (shown as “S” in FIG. 3 ), betweenpositive and negative inputs of the operational amplifier OA, which mayresult in a lowering of impedance between operational amplifier OAinputs. Applicant has observed that presence of shorts is associatedwith noise decrease. Shorts S may also occur in other parts of thecircuity.

Applicant has observed that both failure modes, discontinues and shorts,have unique “noise footprints” that can be detected in noise signalmeasurements when the detector D is idle (with no X-ray incident fromthe source XR) to establish whether or not a given pixel is bad. Anotherfailure mode that may be detected herein is a failure within theoperational amplifier OA that may result in no output reading at all,and thus zero noise.

Other failure modes may also be detected herein, in the above describedexamples for failure modes are not exhaustive. Also, it will beunderstood that the circuitry in FIG. 3 is only for illustration of thevarious failure modes and the noise patterns they may cause. Variants ofthe circuitry, and indeed other circuitry, is also envisaged herein, andthe wiring diagram in FIG. 3 is not to be read as limiting theprinciples described herein. However, some embodiments envisaged hereinmay still include the shown circuitry, or variants thereof, inparticular circuit equivalents thereof.

Reference is now made to FIG. 4 which shows a schematic block diagram ofthe fault checker FC as envisaged herein.

The fault checker FC may be fully integrated into the imager XI, inparticular into the detector module D itself. The fault checker may beimplemented on a single or multiple integrated circuits (“chip”). Thefault checker may be implemented on a micro-controller includingprocessing unit storage and other components necessary for processing.

As briefly mentioned above, the fault checker FC, as indicated in FIG.2A in dotted lines, may tap into the analogue domain circuitry of thedetector so is capable of processing analogue signals. In this case thefault checker's input port IN includes, or is coupled to, ananalogue/digital converter. In particular, in embodiments, fault checkerFC is configured and arranged to collect its input as analog signal(s),in a section of the DAQ circuity downstream (after) the photodiodes PHD,but upstream (before) the DAQ's A/D conversion. However, and as alsomentioned above, alternatively and preferably, the fault checker FCreceives its input after the detector D′s digitalization stage as shownin solid lines in FIG. 2A. In particular, the fault checker FC mayobtain its input from the regular output interface into which the pixelreadout lines terminate. This may be the same output that supplies theimage processor with projection raw data 7E to be reconstructed. Inembodiments the fault checker FC is implemented by a suitably programmedprocessor PU. The processor PU may be dedicated or may programmed toperform other functions also, such as controlling transfer of data tothe image processor IPS, or others.

In short, the proposed fault checker FC is configured to operate inanalogue or digital domain, but operation in digital domain ispreferred. In either case, faults in analog and digital circuitry isdetectable with the proposed fault checker FC.

Some detectors D include a section with logarithmic conversion. Alogarithmic operation is applied to the output signals after A/Dconversion to produce “logged” signals. The proposed fault checker FC isfurther configured to process logged or unlogged signals when checkingfor faults.

Broadly, and with continued reference to FIG. 4 , input signals,including pixel readings in detector idle state, are received at theinput port IN may come from a single pixel or may come from a group ofpixels, such as a tile, or from all pixels on the detector arrays, orfrom other, not necessarily topologically connected groups. Operation ofthe fault checker proceeds pixel-wisely and produces for each pixelsignal processed the respective indication whether the respective pixelis bad or not. This indication per pixel is output at output port OUT.The fault checker may operate in parallel on plural, possibly all or agroup of pixels, or may process the pixel readouts in sequence.

The FC may include a digital high-pass-filter (not shown) to be appliedto the measured pixel signal to enhance noise. This is because it hasbeen found that a spectral density of noise as associated withcapacitance on the input of the amplifier OA in case of discontinuityhas strong frequency dependence.

Operation of the fault checker FC includes a convertor CV to convert thepixel reading signals, analogue or digital, into a metric, a number, tobe explained more fully below. The metric is then processed by acomparator CP that compares the metric against one or more thresholds THaccording to a test policy or uses other text policies. The comparisonagainst one or more threshold may be explicit or implicit. Thethresholds may be fixed or may be dynamically changed for each or somepixels over time and/or change from pixel signal to pixel signal for agiven pixel. The comparator CP checks whether the thresholds orthreshold is violated as per the test policy. Some test policies will bediscussed below at FIG. 5 .

In embodiments, the comparator CP implements a failure test in terms ofone or more thresholds. If the test fails, the respective pixel isconsidered bad and this is flagged up in a suitable data structure whichis then output at port OUT. The per pixel faults BD may be written intoa log-file or may be output individually as a suitable coded flag andthis is then processed/stored by a receiving party. The log-file may bestored in a memory, either onboard the fault checker FC or in externalmemory. The log-file may be displayed on a display device MIT, or mayotherwise be made available. The log file may be transmitted to arecipient, for instance for review by service personnel. The log filemay be transmitted by fault checker FC through a suitable communicationsystem.

In embodiments, the fault checker FC further includes a faultcompensator FCOMP. The fault compensator FCOMP allows continuedoperation of the imager even though faulty pixels have been detected.This is so because a mere sporadic fault occurrence up to a certaincritical number of faulty pixels still allows safe continued operationof the imaging apparatus. If a pixel is known as bad, its reading can bedisregarded and replaced by interpolations from neighboring pixels whichwere flagged up as good. Fault compensator FCOMP may co-operate with theimage processor IPS where the measurement data are re-constructed intoimagery. The fault compensation can be conducted in the image domain orcan be done in the projection domain. For instance, the measurement datain projection domain collected in an imaging operation can be correctedfor bad pixels by interpolation across neighboring measurements and itis the so “patched up” projection data that is then fed into the imageprocessing system for re-construction. Alternatively, the interpolationcan be done in image domain by modifying contributions of bad pixels toa given voxel.

So whilst the output can be used to trigger a signal for a servicecallout, this is not necessary in all circumstances and the proposed FCcan ensure continued safe operation despite bad detectors found. Onlywhen the overall number of BD pixels exceed a certain critical thresholdor when too many BD pixels accumulate in given region, so that noreliable robust interpolation can be guaranteed, is a service callissued. This can be done by the FC fully automatically by interfacingwith a suitable communication system. A message including imager type,location, etc may be send to a service point to request the call-out.

Reference is now made to FIG. 5 which shows a flow chart of acomputer-implemented method for fault checking an X-ray detector. Thesteps in the flow chart illustrate operation of the fault checker ofFIG. 4 in more detail. However, it should be understood that the belowdescribed method and its steps constitute a teaching in their own right,and are not necessarily tied to the architecture of FIG. 4 .

At step S510 and idle state of the X-ray imager XI is detected. This canbe done by an event handler that intercepts a switch signal issued forinstance by a user from an operator console associated with the imagerXI. The switch signal may have been issued by the user specifically byoperating a “check detector” button, or other interface after the X-raytube has been switched off by the user. In addition or instead, faultchecking mode is automatically enabled once the event handler interceptsa switch signal for switching off the X-ray source. Switching off theX-ray source may include interrupting the power supply to the source.However, operating a collimator to block out the X-ray beam may alsocause the detection of the imager's XI idle state and may trigger thefault check.

In more detail, the idle state as envisaged herein implies in particularthat no x-radiation impinges on the detector pixels (elements) PX1, PX2to be fault checked, and that no scan is expected for a preset period oftime. Preferably the event that triggers fault checking mode is notmerely sent when the X-ray is off, as in some imaging protocols, X-rayis switched off and on, or is collimated out several times during theimaging procedure. Preferably then, the fault check triggering eventindicates not only X-ray switch off, but in addition that the imager isnot in an ongoing imaging procedure and/or that such an imagingprocedure is not expected to happen within the said preset time, such aswithin the next minutes, next half an hour, next hour, or any othersuitable off-duty period. This is to ensure not to degrade systemperformance because of fault checking and parameter reset. There may bea user interface, such as an override button or other, that allows auser to anytime interrupt the fault checking mode and request returningto imaging mode. Alternatively, when imaging mode is requested, thefault checking mode is automatically suspended.

At step S520 detection modes (detection parameters) of the detector aresuitably set to now process in idle state. Normally, the detector pixelreadings at idle state are not collected or analyzed. However, in theproposed method pixel readings outside the scan time are obtained.Setting the detection modes facilitates noise collection by settingdetection parameters to optimized values, that is, to values thatfacilitate noise measurement collection. In particular, and inembodiments, the detection parameters are set so that noise added by thecapacitance of the detecting element, eg photodiode PHD, at the input ofthe detector channels may be identified from the overall channel noise.The setup is aimed, in some (but not all) embodiments, specifically tomake a contribution of noise from the PHD capacitor detectable, comparedto the overall noise. Specifically, the setup is aimed to reducecontribution from other noise sources. Yet more specifically, this setupmay include any one or more of: setting a gain of the detector channelto be processed, the integration time (for integrating detection). Inaddition or instead, other detection parameters are adjusted, such asthe length of the time period over which the series readings arecollected, on which more further below at step S540.

At step S530, analogue or, preferably, digital signals for a giventarget pixel are measured. The measurements (“readings”) include noisemeasurements as there is no X-ray exposure due to the imager being inidle state. The proposed method will be explained in the following atthe example of a certain given target pixel, with the understanding thatthe method is to be carried out in the same manner on some or all pixelsof the whole detector or part thereof, such as some or all pixels on agiven detector tile or part thereof, or on any other portion of thedetector array. The proposed method may be practiced in parallel forplural pixels, or may be practiced in sequence for some pixels. Evenwhen practiced in parallel, this may include processing different groupsof pixels in sequence.

The noise measurements can be obtained in a time series for the targetpixel over a period of time at a given frequency. The collection ofpixel readings in step S530 at idle state may be implemented byinterfacing with existing output ports of DAQ system that are used forthe normal scans in busy, on-duty, state. Specifically, the noisereadings for any pixels may be obtained in the digital domain assupplied by the read-out circuitries SE.

Alternatively, the measurement signals may be collected in the analogdomain, further upstream in the pixel electronics PE1 of the targetpixel PX. The detector D as envisaged herein is configured such thatreadings are delivered despite the imager XI being in idle mode, toensure that data can be collected in step S530 for fault-checkingpurposes. In other words, whilst the X-ray source may remain switchedoff during execution of the proposed method, in particular during themeasurement collection step S530, the detector itself remains powered onso that the readings can be generated, as explained in FIG. 3 above.Step S530 may be implemented by one or more dedicated chips, such as amicrocontroller or microprocessor, embedded in the detector modulesystem D.

At step S540, based on the measurements for the target pixel, a metricis computed. The metric is a suitably chosen statistic or other quantitythat captures characteristics of noise fluctuation. In particular, themeasurement of the target pixel includes measuring multiple readings atstep S530 for the target pixel over a time series of a given length. Itis this time series of noise measurements that are then used in stepS540 to calculate a statistical metric, such as sums of differences or astandard deviation, the square thereof (variance), or other, highermoments, such as the 3r^(d) or 4 ^(th) moments (skewness, kurtosis,respectively), or others still, such as autocorrelation, entropy, mixedmoments, a combination or any two or more of the foregoing, or any othersuitable quantity, statistical or not. The metric is preferably suitablyto quantify fluctuations and/or noise, in particular noise fluctuations.

In embodiments of said metric, the readings of the target pixel channelare collected over time and a statistical standard deviation iscalculated. As mentioned earlier in FIG. 4 , a digital high-pass-filtermay be applied first to enhance noise contribution in the measured pixelreadings due to the correlation of frequency and spectral density ofnoise.

In an optional step S550, the metric is normalized. This may includetaking into account readings collected over time at a group of one ormore pixels other than the target pixel. The measurement collection forsuch pixels is the same as described above at step S530. The group mayconstitute pixels on the same tile, may constitute immediate neighboringpixels or may constitute any other one or more groups elsewhere (moreremote) on the detector. The group of pixels may be hence referred to asreference pixels relative to the target pixel. Normalizing the metricfor a given target pixel based on using measurements from referencepixels (reference group) allows compensating factors such as the agingof the detector system. Using local, for example neighboring pixels, asthe reference group can compensate for local effects. In particular,using as reference group some or all channels that are served by thesame shared circuitry SE, eg an ASIC, may allow compensating for changesrelated to the ASIC's power supply, or the ASIC's local temperature. Ingeneral, using as reference group such channels that experience the sameconditions as the target channel makes the thresholding more robust.

As mentioned above at step S520, another detection parameter that mayadjusted is the length of the period over which pixel readings arecollected, and based on which the metric, such as the standarddeviation, is computed. The collected pixel readings may be consideredoutcomes of a random variable. In general, for a random variable, anaccuracy of evaluating the standard deviation from measurements improvesas the number of readings over time increases. However, a series ofreadings taken over too long a time period might be affect by lowfrequency noise that might cause drift, which in turn might change themean reading of a channel, and interfere with a metric's ability tocorrectly capture noise. Normalizing the channel noise as done in stepS550 by using readings from other channels may be used to compensate forsuch low frequency drift. Normalization S550 may be used also tocompensate for changes in the environment conditions, and for the agingof the detector system D.

In embodiments, the array of detector pixels is made up from groups ofpixels such those pixels on a given tile, that share the same electroniccircuits SE, such as a single ASIC for A/D conversion. For such groupsof channels that are served by the same shared electronics, the same orsimilar noise characteristics may be expected, and hence one may expectsimilar values for the noise metric such as mean absolute differencebetween logged readings or other of the above mentioned metricembodiments. In this case, the normalization S550 may be carried overchannels served by to the same ASIC, instead of the using the entirepixel array of the detector module D. In such embodiments, thenormalization may be done per group, such as per tile.

At step S560 the test policy is applied. One test policy may includethresholding. At step S560 one or more thresholds are applied againstthe calculated metric at step S540 or its normalized version as obtainedin step S550. Specifically, in embodiments the thresholding may includechecking whether the respective quantity/metric for the target pixel PX1is above or below the threshold. Two or more thresholds may be used todefine a range and it is checked whether the metric quantity obtained insteps S540, S550 is within the range or is outside the range.

In step S570, based on the test policy, a decision is reached on whetherthe target pixel PX1 is BD or not. It will be understood that the testpolicy will depend on the semantics of the metric, that is on how thenoise is measured. For example, in the embodiments mentioned above inrelation to the standard deviation as metric, this may be comparedversus either a low threshold or a high threshold or both, low and highthresholds. Comparison with low threshold may detect discontinuities atthe input of the detecting channels amplifiers. So if the metric valuescome out under the lower threshold, the target pixel is BD, and goodotherwise. If two thresholds are used, may check in addition that themetric is not too high, as this too may indicate BD. Specifically, ifthe metric come out higher than the high threshold, this may identifyshorts at the input of the detecting channels amplifiers, or faults inthe amplifier or in other electronics circuits. Similar conclusion maybe reached by a metric other than the standard deviation.

In step S580, based on the decision at step S580, the target pixel isflagged up as bad BD or as good (“OK”). This step may includeconstructing or writing into a suitable data structure such as a tablewhere a pixel identifier entry is associated with the correspondingflag, such as “BD” or “OK”, or “1”/“0” or other according to a suitableencoding. Alternately, the list includes only the BD pixel identifiersor only the good pixel identifiers.

There may be a further optional step of checking, based on the datastructure, whether a critical number of bad pixels has been reachedglobally and/or for a certain neighborhood. If yes, an alarm is issuedand/or a call out service is requested and the imager is taken offservice. If not, the imager is allowed to continue, and interpolationmay be used to compensate the bad pixels if the imager exits idle stateand (re-)enters regular imaging operation (“duty state”) which includesswitching back on the X-ray source. It will be understood that the saidlist (or other data structure, such as a database entry) which recordsthe bad pixels, is maintained during busy state, and is continuedwritten to once the imager retires into idle state again and the methodis reapplied.

The method may be executed each time the imager retires into idle state.Alternatively, the method is executed according to a schedule, forexample once per hour, day, week etc, when the imager is in idle state,or according to an explicit demand. The method, when executed,determines the status (BD or OK) for each pixel once or more than once.Specifically, in one embodiment the method is executed continuously, ata given frequency such as per second, whilst the imager XI is in idlestate. Other periodic, albeit slower, schemes are also envisaged, suchas per minute or per hour evaluations, etc, whilst the imager XI is inidle state.

In general, the proposed method may be performed at once for all pixels,or the detector array is processing per portion over time. Specifically,to save processor FC resources, each part of the detector array ischecked one after the other in cycles, until the whole array D has beenfault-checked. Once pixels in all of the detector have been checked, thechecking cycle restarts with (re-)checking pixels in the part of thedetector first processed, and so on. If the flow of the fault checkingmethod is interrupted, eg, when a switching out of idle state isrequested, once idle state is restored, the method flow will re-startfault checking in the same part of the detector array left beforeinterruption. This fault-checking protocol assures that, over time, theentire detector D will be fault-checked eventually.

It will be understood that the above described processing in parts willdepend on the processor capability on which the fault checker isimplemented. In embodiments, processing in parallel the entire detectorarray may be possible and this is indeed preferred. Preferably, theprocessing manner (in parts or at once, in series or in parallel) andthe processing capability of the processor are adjusted and chosen,respectively, so that a complete detector array fault-check can be donewithin a period less than an average off-duty time between patientimaging in a given clinical site.

Step S540 and step S550 will now be explained in more detail asenvisaged in embodiments.

An example implementation may be used for a rectangular detection arraycomprising 672 by 128 channels, of an integrating type detector. Thechannels are set to integration time of 3000. A number of noise readingsare collected, e.g. 4000 of the target channel with no X-ray exposure.

Denoting the n^(th) reading of a channel at the i^(th) detector columnand the j^(th) detector row by x_(i,j,n), the standard deviation of xalong the readings is calculated.

The standard deviation (of noise) at the i^(th) detector column and thej^(th) detector row may be denoted as N_(i,j). N_(i,j) represents themetric as calculated at step S540 in embodiments and this can becompared against or more thresholds to conclude the pixel is BD or not.

For better robustness it is proposed herein in preferred embodiments tonormalize N_(i,j) at step S550 based on readings from a reference groupof other channels. In embodiments, readings from all other channels arecollected based on forming a quotient of N_(i,j) and medians over rowsand columns. Specifically, in embodiments the median of noise alongcolumns is computed and used to normalize:

S _(i,j) =N _(i, j)/median_(aiong index i)(N _(i,j))   (1)

In addition, the median along rows of S_(i,j) is computed and the usedfor normalizing to find the normalized noise as:

NN _(i,j) =S _(i,j)/median_(along index j)(S _(i,j))   (2)

The following variations in relation to (1), (2) are envisaged inembodiments: the medians may not need to be collected over all rows orover all columns, so i and j may be restricted, to cover for instanceonly pixels for a given tile or any other group. In embodiments, onlythe four or eight immediate neighbors in the matrix layout FIG. 2B areconsidered for normalization, or a slightly larger group, such as the asquare of given edge length that includes the target pixel in itscenter, etc. Other neighborhood geometries are also envisaged. Infurther alternative embodiments, only column medians or only row mediansare considered in embodiments instead of row and column medians as in(2). Normalizations based on quantities other than medians may be usedin (1), (2), such as averages, weighted averages, percentiles, etc.

In alternative embodiments, instead of using the standard deviationN_(i,j) over readings over time, a high-pass-filter is applied, forinstance, by calculating, as a metric, the standard deviation of the ofneighboring differences (x_(i,j,n)−x_(i,j,n−1)).

The normalized noise metric such as (1) or (2) or other metrics may becompared in S560 against one threshold or multiple thresholds. The valueof a (lower) threshold may depend on the expected contribution of thecapacitance of the detecting element PHD to the overall noise. A typicalvalue may be 0.85. A higher threshold may be applied as well. If forinstance, it is found that the noise in a functioning channel group iswithin 0.85 to 1.2 times the median noise (or other average) of thepixels in the group, a high threshold value of 1.5 times the mediannoise of the pixels in the group may be set.

The above described embodiments (1),(2) of computing S540 the noisemeasuring metric and/or the normalization step S550 can be refined toconsume less memory and/or to be applicable also for the processing oflogged signals.

Storing the required number of readings per channel e.g. 4000 readingsper channel, for calculating the noise as per (1) or (2) for example,may pose substantial demands on the system memory. It is desired to usean algorithm that allows accumulating data from multiple readingswithout significant increase in the required memory. Anotherconsideration is that in some systems, the digital output from the CTdetectors is the logarithm of the signal. It is advantageous to use analgorithm that is capable to use as input either the (unlogged) signalor the logged signal.

An alternative to (1), (2) is described in the following that allowsaccumulating data from multiple readings for memory savings, and mayaccept with similar performance, either unlogged signals or the loggedsignals.

As above in (1), (2), an example implementation may be used for arectangular detection array comprising 672 by 128 channels, ofintegrating type detectors. The channels may be set to integration timeof 3000 or other.

A number Q of readings is collected in step S530, e.g. Q=4001 of thetarget channel with no X-ray. Denoting the log of the n^(th) reading ofa channel at the i^(th) detector column and the j^(th) detector row byLx_(i,j,n), the sum of the absolute value of difference betweensuccessive readings is calculated. The sum of Q−1 absolute differencesat the i^(th) detector column and the j^(th) detector row may then bewritten for this new metric as:

s _(i,j)=Σ_(n=1) ^(Q−1)abs(Lx _(i,j,n) −Lx _(i,j,n−1))   (3)

In the normalization step S550, one may calculate the median of sumalong columns and normalize as:

S _(i,j) =s _(i,j)/median_(along index i)(s _(i,j))   (4)

In addition or instead, one may calculate the median along rows ofS_(i,j) and normalize to find the normalized noise metric for thisembodiment as:

NN _(i,j) =S _(i,j)/median_(along index j)(S _(i,j))   (5)

It will be appreciated that for the calculations (4),(5), one may use asinput the log of the signal but may instead use the (unlogged) signal.In addition, accumulating readings by summation now requires only onememory cell per channel, and one may use a single readings countercommon for all channels accumulated, as opposed to retaining n time mmemory cells (m being the number of readings for each of n channels) asmay be required for (1),(2). The configuration (3)-(5) may significantlyreduce the required memory and calculation complexity compared tocalculating the noise as per (1) or (2). Again, in (4),(5), a quantityother than the median may be used, eg other averages, possibly weighted,or others still.

In embodiments, the summation operation in (1)-(5) is performed in partsby the fault checker FC, and in parts by the common detector circuitrySE or other detector D circuitry. The processor FC may receive a partialsum from the detector D circuitry as required by (1)-(5). This“outsourcing” in parts, reduces the data volume to be transferred fromthe detector D to the processor FC, and the load on processor FC.Alternatively, all summation work is done either by the detector Delectronics or is done by the fault checker FC.

Instead of forming the sum of differences in (5), one may also form aweighted sum of said differences, with a respective weight w_(i)multiplied with each or some of the summands in (4),(5). In this manner,same readings may be given more weight than others, to so account forchanges in the environment whilst the readings are taken for example.

The thresholding at S560 is as described above for (1) and (2): thenormalized sum (5) is compared against one threshold or multiplethresholds. The value of the lower threshold may depend on the expectedcontribution of the capacitance of the detecting element to the overallnoise. Again, a typical value may be 0.85. High threshold may be appliedas well. The above mentioned variations in relation to (1), (2), are ofequal application to (3)-(5).

As to the one or more thresholds at step S570, this/these may bepre-defined and calculated from design parameters of the detector D,such as characteristics of the photodiodes PHD and/or for the amplifierOA, or of any other relevant electronic component, depending on the typeof fault one wishes to check for. Alternatively, the thresholds may bedetermined experimentally. As mentioned above, a value of less than 1but greater 0.5, such as 0.8, 0.85, 0.9 may be used for some detectors.Multiple thresholds can help identify multiple root causes or failuremodes, e.g. value below 0.85 points to a discontinuity at the photodiodePHD, while a value below 0.5 points to a failure in operationalamplifier OA. The threshold values may be fault specific. It will beunderstood that the specific values referred to herein are exemplary,and other values are also envisaged herein, although the mentionedvalues may still be included in embodiments.

Preferably, a dynamic threshold is used. Different threshold adaptationpolicies may be used. In one embodiment, this is implemented bymodifying a given, pre-defined, initial threshold based on an average ofthe metric for the group of reference pixels. In embodiments, the metricmay be the same as used for measuring the noise in step S540, such assums of absolute successive differences or the over-time standarddeviations, etc.

More specifically, in embodiments, the adapted threshold may be set asthe current threshold (which may initially be set to the pre-definedone) times the median or other average (possibly weighted) overreference channels of the same metric, such as the sum of absolutedifferences or the standard deviation. In other words, the threshold(s)may change in general over measurement cycles. However, in otherembodiments, the current threshold is only adapted if the metric (suchas the sum of absolute differences or the standard deviation) for thegiven target channel is actually greater than the current thresholdvalue.

In preferred embodiments, the data computed for the normalization can beused to dynamically change the threshold as described, using the samemetric. The reference group for the purpose of computing thenormalization is the same as the reference group for the purpose ofadapting the threshold. However, this is not necessarily so in allembodiments, where the groups may differ for the two purposes.

As an alternative to adapting the threshold(s) in each measurement cycleS530, the threshold is fixed once and is then maintained. Alternately,the threshold is adapted periodically, e,g, when the imager XI ispowered on or according to other schedules, once per hour, once perweek, etc.

It should be understood that the above described method/algorithm can bepracticed in a number of different embodiments, all envisaged herein.Such embodiments may include different acquisition schemes of the data,e.g. collect the data only from a part of the detector array D at a timeas mentioned earlier. Another embodiment that may save memory, is that,instead of storing the complete data from multiple readings, it is onlysome statistical properties of the data that is stored, such as mean andvariance, from the whole or part of the readings per channels. Thestatistical parameters from two or more groups of readings may becombined together to improve the accuracy of estimating the noisewithout significantly increasing memory usage.

Also, it will be understood that the threshold decision policiesdescribed above, that is, whether a result being over or below athreshold is taken to indicate the target pixel being considered faulty,will depend on the manner in which the metric is computed, on the typeand semantic of the metric, and possibly on other design factors.

Whilst in the above processing of the noise readings was described forthe time domain, in some embodiments the processing is done in frequencydomain. The noise measurements are first Fourier-, Laplace- orWavelet-transformed into frequency signals in a spectral diagram, andthe frequency signals may then be processed similar to what has beendescribed above by computing a suitable metric that can capture faultrelated time domain fluctuations in frequency domain, or that cancapture fault-specific noise footprints in frequency domain. However,the fault check analysis in time domain as described herein ispreferred.

Reference is now made to FIG. 6 which shows a plot of a point cloud in atwo dimensional coordinate system. The plot FIG. 6 demonstrates theefficiency of the proposed method. The normalized noise was calculatedas described above. In addition, signals Y with X-ray on were measuredand normalized. Note that the signal measurement with X-ray on, asrecoded on Y the axis is shown only for illustration purposes and is notusually needed when the method is applied. Each channel in the detectorarray is represented by a point in FIG. 6 . The X-coordinate of thepoint corresponds to the normalized noise of the channel and theY-coordinate corresponds to the channel signal with X-ray. The verticaldashed line corresponds to a normalized noise threshold value of 0.85.The horizontal dashed line corresponds to an arbitrary threshold for“low signal” set for the normalized signal of 0.6. It can be seen thatmost of the channels having low normalized signal (below 0.6) are alsobelow (on the left of) the normalized signal. Hence it is possible witha high success rate to find most of the low signal channels, that is, BDpixels, from measuring the noise as proposed herein. And this highsuccess rate can still be achieved without X-ray exposure. It can beseen that only two low signals channels are missed. These two low signalchannels may result from other faults types than discontinuities at theinput of the channel amplifier or shorts. However, identifying such“rogue” faults and setting the threshold and choosing a metricaccordingly may result improve fault detection success rate evenfurthers still.

The components of the fault checker FS may be implemented as one or moresoftware modules, run on a general purpose computing unit PU such as aworkstation associated with the imager XI, or on a server computerassociated with one or a group of imagers arranged in a distributedarchitecture and connectable in a suitable communication network.Alternatively, some or all components may be arranged in hardware suchas a suitably programmed microcontroller or microprocessor, such an FPGA(field-programmable-gate-array) or as a hardwired IC chip, anapplication specific integrated circuitry (ASIC), integrated into thedetector module D or otherwise integrated into the imaging system XI. Ina further embodiment still, the fault checker may be implemented inboth, partly in software and partly in hardware. One or more featuresdescribed herein can be configured or implemented as or with circuitryencoded within a computer-readable medium, and/or combinations thereof.Circuitry may include discrete and/or integrated circuitry, asystem-on-a-chip (SOC), and combinations thereof, a machine, a computersystem, a processor and memory, a computer program.

In another exemplary embodiment of the present invention, a computerprogram or a computer program element is provided that is characterizedby being adapted to execute the method steps of the method according toone of the preceding embodiments, on an appropriate system.

The computer program element might therefore be stored on a computerunit, which might also be part of an embodiment of the presentinvention. This computing unit may be adapted to perform or induce aperforming of the steps of the method described above. Moreover, it maybe adapted to operate the components of the above-described apparatus.The computing unit can be adapted to operate automatically and/or toexecute the orders of a user. A computer program may be loaded into aworking memory of a data processor. The data processor may thus beequipped to carry out the method of the invention.

This exemplary embodiment of the invention covers both, a computerprogram that right from the beginning uses the invention and a computerprogram that by means of an up-date turns an existing program into aprogram that uses the invention.

Further on, the computer program element might be able to provide allnecessary steps to fulfill the procedure of an exemplary embodiment ofthe method as described above.

According to a further exemplary embodiment of the present invention, acomputer readable medium, such as a CD-ROM, is presented wherein thecomputer readable medium has a computer program element stored on itwhich computer program element is described by the preceding section.

A computer program may be stored and/or distributed on a suitable medium(in particular, but not necessarily, a non-transitory medium), such asan optical storage medium or a solid-state medium supplied together withor as part of other hardware, but may also be distributed in otherforms, such as via the internet or other wired or wirelesstelecommunication systems.

However, the computer program may also be presented over a network likethe World Wide Web and can be downloaded into the working memory of adata processor from such a network. According to a further exemplaryembodiment of the present invention, a medium for making a computerprogram element available for downloading is provided, which computerprogram element is arranged to perform a method according to one of thepreviously described embodiments of the invention.

It has to be noted that embodiments of the invention are described withreference to different subject matters. In particular, some embodimentsare described with reference to method type claims whereas otherembodiments are described with reference to the device type claims.However, a person skilled in the art will gather from the above and thefollowing description that, unless otherwise notified, in addition toany combination of features belonging to one type of subject matter alsoany combination between features relating to different subject mattersis considered to be disclosed with this application. However, allfeatures can be combined providing synergetic effects that are more thanthe simple summation of the features.

While the invention has been illustrated and described in detail in thedrawings and foregoing description, such illustration and descriptionare to be considered illustrative or exemplary and not restrictive. Theinvention is not limited to the disclosed embodiments. Other variationsto the disclosed embodiments can be understood and effected by thoseskilled in the art in practicing a claimed invention, from a study ofthe drawings, the disclosure, and the dependent claims.

In the claims, the word “comprising” does not exclude other elements orsteps, and the indefinite article “a” or “an” does not exclude aplurality. A single processor or other unit may fulfill the functions ofseveral items re-cited in the claims. The mere fact that certainmeasures are re-cited in mutually different dependent claims does notindicate that a combination of these measures cannot be used toadvantage. Any reference signs in the claims should not be construed aslimiting the scope.

1. A fault checker system for an X-ray detector, comprising: an inputinterface for receiving readings acquired by a target detector pixel notexposed to X-radiation; a converter configured to perform a conversionoperation to convert the readings into a metric; and a thresholderconfigured to compare the metric against at least one threshold and,based on the comparing, providing an indication on whether the targetdetector pixel is faulty wherein the metric is configured to capturenoise fluctuation.
 2. The system of claim 1, wherein the performing ofthe conversion operation by the converter includes the converterperforming a normalization operation applied to the readings.
 3. Thesystem of claim 2, wherein the normalization operation relates readingsfrom a group of one or more pixels, to the readings acquired by thetarget pixel.
 4. The system of claim 3, wherein the group of pixelsneighbor the target pixel.
 5. The system of claim 1, wherein the metricis configured to quantify a fluctuation in the acquired readings.
 6. Thesystem of claim 1, wherein the metric includes i) an estimate of anover-time standard deviation, and/or ii) a sum of absolute differences.7. The system of claims 2, wherein the normalization operation includesforming spatial medians for readings in the said group of one or morepixels.
 8. The system of claim 1, wherein the target pixel is includedin a detector tile, and wherein the neighboring pixels are restricted tothe detector tile.
 9. A method of fault checking an X-ray detector,comprising: receiving readings acquired by a target detector pixel notexposed to X-radiation; converting the readings into a metric; andcomparing the metric against at least one threshold and, based on thecomparing, providing an indication on whether the target detector pixelis faulty, wherein the metric is configured to capture noisefluctuation. 10-14. (canceled)
 15. A non-transitory computer-readablemedium for storing executable instructions, which cause a method to beperformed to fault check an X-ray detector, the method comprising:receiving readings acquired by a target detector pixel not exposed toX-radiation; converting the readings into a metric; and comparing themetric against at least one threshold and, based on the comparing,providing an indication on whether the target detector pixel is faulty,wherein the metric is configured to capture noise fluctuation.